Covid Report for Family

Background

Notes and format last updated Apr 16, 2020

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	New York	16,397
2	New Jersey	14,441
3	Massachusetts	10,023
4	Rhode Island	9,111
5	Connecticut	8,406
6	District of Columbia	7,325
7	Louisiana	6,382
8	Delaware	5,430
9	Illinois	5,037
10	Michigan	4,398
11	Maryland	4,368
12	Pennsylvania	4,139
13	Nebraska	3,166
14	Iowa	3,075
15	Indiana	3,046
16	South Dakota	3,015
17	Colorado	2,917
18	Georgia	2,670
19	Mississippi	2,646
20	Virginia	2,283
21	Washington	2,058
22	Tennessee	1,953
23	New Mexico	1,922
24	New Hampshire	1,903
25	Kansas	1,841
26	Nevada	1,826
27	Ohio	1,751
28	Florida	1,717
29	Utah	1,661
30	Alabama	1,654
31	North Dakota	1,607
32	Vermont	1,445
33	Missouri	1,429
34	California	1,425
35	Wisconsin	1,414
36	South Carolina	1,312
37	Minnesota	1,282
38	Arizona	1,225
39	Kentucky	1,200
40	Arkansas	1,149
41	Texas	1,142
42	North Carolina	1,131
43	Idaho	1,089
44	Oklahoma	1,021
45	Maine	896
46	Wyoming	767
47	West Virginia	682
48	Oregon	654
49	Puerto Rico	577
50	Alaska	503
51	Hawaii	432
52	Montana	427

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	New Jersey	265
2	District of Columbia	241
3	Massachusetts	230
4	Nebraska	221
5	Rhode Island	217
6	Illinois	204
7	Iowa	192
8	New York	182
9	Maryland	161
10	Delaware	126
11	Connecticut	113
12	Virginia	101
13	Kansas	100
14	Indiana	92
15	Minnesota	88
16	Pennsylvania	84
17	New Mexico	82
18	Mississippi	74
19	Tennessee	72
20	Louisiana	68
21	New Hampshire	68
22	Colorado	65
23	Georgia	60
24	Alabama	55
25	South Dakota	53
26	Michigan	52
27	Wisconsin	52
28	North Dakota	51
29	Utah	51
30	Missouri	50
31	Ohio	49
32	Arizona	43
33	Nevada	40
34	Kentucky	36
35	California	33
36	Florida	33
37	South Carolina	32
38	Texas	32
39	North Carolina	30
40	Washington	29
41	Puerto Rico	28
42	Oklahoma	24
43	Maine	20
44	Arkansas	17
45	Oregon	14
46	West Virginia	13
47	Wyoming	13
48	Vermont	12
49	Idaho	11
50	Alaska	2
51	Montana	1
52	Hawaii	0

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New York	998
2	New Jersey	890
3	Connecticut	716
4	Massachusetts	593
5	Louisiana	428
6	Michigan	414
7	District of Columbia	365
8	Rhode Island	321
9	Pennsylvania	224
10	Illinois	210
11	Maryland	201
12	Delaware	186
13	Indiana	170
14	Colorado	147
15	Georgia	115
16	Washington	111
17	Mississippi	104
18	Ohio	90
19	Nevada	86
20	Vermont	84
21	Virginia	80
22	Minnesota	75
23	New Mexico	74
24	Florida	65
25	Missouri	63
26	New Hampshire	63
27	Alabama	60
28	Oklahoma	60
29	Iowa	59
30	Kentucky	59
31	California	58
32	Wisconsin	58
33	South Carolina	54
34	Kansas	52
35	Arizona	49
36	North Carolina	43
37	Maine	42
38	Nebraska	40
39	Idaho	35
40	North Dakota	32
41	Tennessee	32
42	Texas	31
43	West Virginia	27
44	Arkansas	26
45	Oregon	25
46	South Dakota	23
47	Puerto Rico	16
48	Utah	15
49	Montana	14
50	Hawaii	12
51	Wyoming	12
52	Alaska	9

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	Connecticut	20
2	Rhode Island	19
3	Massachusetts	18
4	New Jersey	13
5	New York	13
6	District of Columbia	12
7	Michigan	8
8	Delaware	7
9	Maryland	6
10	Illinois	5
11	Pennsylvania	5
12	Indiana	4
13	Louisiana	4
14	Virginia	4
15	Minnesota	3
16	Mississippi	3
17	New Mexico	3
18	Georgia	2
19	Kansas	2
20	Arizona	1
21	Arkansas	1
22	California	1
23	Colorado	1
24	Florida	1
25	Iowa	1
26	Kentucky	1
27	Missouri	1
28	Nebraska	1
29	Nevada	1
30	New Hampshire	1
31	North Carolina	1
32	Ohio	1
33	South Carolina	1
34	Vermont	1
35	Alabama	0
36	Alaska	0
37	Hawaii	0
38	Idaho	0
39	Maine	0
40	Montana	0
41	North Dakota	0
42	Oklahoma	0
43	Oregon	0
44	Puerto Rico	0
45	South Dakota	0
46	Tennessee	0
47	Texas	0
48	Utah	0
49	Washington	0
50	West Virginia	0
51	Wisconsin	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Trousdale	Tennessee	119,461	1	99
Lincoln	Arkansas	64,650	2	99
Dakota	Nebraska	50,185	3	99
Nobles	Minnesota	46,743	4	99
Bledsoe	Tennessee	39,697	5	99
Davidson	Tennessee	4,597	211	93
Richland	South Carolina	2,350	520	83
Pierce	Washington	1,692	729	76
Orange	California	900	1212	61
York	South Carolina	790	1350	57

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Randolph	Georgia	2,803	1	99
Terrell	Georgia	2,462	2	99
Early	Georgia	2,355	3	99
Nassau	New York	1,637	4	99
Essex	New Jersey	1,617	5	99
Richland	South Carolina	101	499	84
Pierce	Washington	57	760	75
Davidson	Tennessee	42	921	70
Orange	California	18	1267	59
York	South Carolina	11	1386	55

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.